Paper
8 June 2022 Functional data analysis of the RF tactical data
Author Affiliations +
Abstract
The tactical edge, with its complicated electromagnetic environment is a very important part of the defense operations. In general, it contains a mix of friendly and adversarial radio frequency signal sources. A method for distinguishing the signals in the tactical arena will be very useful for telling blue and red teams apart. The function data analysis (FDA) methods offer a promising approach to find their underlying signatures. The FDA contains techniques for understanding and analyzing large and complex datasets with hidden underlying properties. It is particularly useful in situations in which one records the data continuously during a time interval or intermittently at several discrete time points. It can also uncover nonlinear functional dependence hidden in such data.

In current work, we use FDA techniques to uncover the hidden continuous functions in the noisy field data. The measured data is a result of the combination of the signal and noise introduced by solar, atmospheric, and other electromagnetic signals present in the surrounding. The report consists of general theory behind FDA (Section 2), steps in the analysis of the field data (Section 3), and numerical results (Section 4). Finally, in Section 5 we summarize the results and point out the next steps.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Vinod K. Mishra and Bhikhari Tharu "Functional data analysis of the RF tactical data", Proc. SPIE 12122, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXI, 121220L (8 June 2022); https://doi.org/10.1117/12.2619001
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KEYWORDS
Smoothing

Data analysis

Data modeling

Error analysis

Interference (communication)

Algorithm development

Electromagnetism

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